Submission¶

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [169]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px

init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [171]:
#load data
df = px.data.gapminder()
df.head()
Out[171]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:¶

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [172]:
# YOUR CODE HERE
df_2007 = df[df["year"] == 2007][["continent", "pop"]]
df_cont = df_2007.groupby("continent").sum().sort_values("continent")
print(df_cont.head())

fig = px.bar(df_cont, x="pop", color=["blue", "red", "yellow", "purple", "orange"], text_auto='.2')
fig.show()
#category_orders={"contintent":["Africa", "Americas", "Asia", "Europe", "Oceania"]}
                  pop
continent            
Africa      929539692
Americas    898871184
Asia       3811953827
Europe      586098529
Oceania      24549947

Question 2:¶

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [173]:
# YOUR CODE HERE
fig.update_yaxes(categoryorder="total ascending")
fig.show()

Question 3:¶

Add text to each bar that represents the population

In [174]:
# YOUR CODE HERE
fig.show()

Question 4:¶

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [175]:
# YOUR CODE HERE

df_sum = df[["continent", "year", "pop"]].groupby(["continent", "year"]).sum("pop").reset_index()
fig = px.bar(df_sum, x="pop", y="continent", color="continent",
  animation_frame="year", range_x=[0,4000000000])
fig.update_yaxes(categoryorder="total ascending")
fig.show()

Question 5:¶

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [176]:
# YOUR CODE HERE
df_sum2 = df[["country", "year", "pop"]].groupby(["country", "year"]).sum("pop").reset_index()
fig = px.bar(df_sum2, x="pop", y="country", color="country", animation_frame="year", )
fig.update_yaxes(categoryorder="total ascending")
fig.show()

Question 6:¶

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [177]:
# YOUR CODE HERE
fig.update_layout(height=1000)
fig.show()

Question 7:¶

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [182]:
# YOUR CODE HERE
fig.update_yaxes(range=[131.5, 141.5])
fig.update_layout(height=500)
fig.show()
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